plot(sort(r05),type='o',main='S&P500 1950-present returns <= -5%')###################################################
Although the frequency of such occurrences is arguably rare, the 1987 drop is much more worthy of the 1 day label 'plunge.'

One other disturbing observation in the data, however, is the large temporal clustering of occurrences in the recent 2008 region. Now that's behavior to be concerned about (not to mention revised flash crash data pts.).

Stephen,If you have a yahoo symbol you can justuse with TNX 10yr as example:library(quantmod)getSymbols("^TNX")

Alternatively, you can go to a historical site like http://www.federalreserve.gov/releases/h15/data.htm then download the file of interest locally to your drive as a .csv file.You can then read and clean up into R as a time series object.

About Me

I've been trading full time for over 10 years and wish to share some of the knowledge I've acquired with others.
I have a particular interest in machine learning and how the current research in this area holds much unexplored potential towards the area of systematic trading development.
Although I've studied many different texts on machine learning, I've often found sparse practical examples related to trading. My goal is to share some concrete examples for the layman to be able to build and replicate.
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intelligenttradingtech@yahoo.com